R for Marketing Research and Analytics Front Cover

R for Marketing Research and Analytics

  • Length: 454 pages
  • Edition: 2015
  • Publisher:
  • Publication Date: 2015-03-10
  • ISBN-10: 3319144359
  • ISBN-13: 9783319144351
  • Sales Rank: #190739 (See Top 100 Books)
Description

This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis.

Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis.

With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

Table of Contents

Part I Basics of R
Chapter 1 Welcome to R
Chapter 2 An Overview of the R Language

Part II Fundamentals of Data Analysis
Chapter 3 Describing Data
Chapter 4 Relationships Between Continuous Variables
Chapter 5 Comparing Groups: Tables and Visualizations
Chapter 6 Comparing Groups: Statistical Tests
Chapter 7 Identifying Drivers of Outcomes: Linear Models

Part III Advanced Marketing Applications
Chapter 8 Reducing Data Complexity
Chapter 9 Additional Linear Modeling Topics
Chapter 10 Confirmatory Factor Analysis and Structural Equation Modeling
Chapter 11 Segmentation: Clustering and Classification
Chapter 12 Association Rules for Market Basket Analysis
Chapter 13 Choice Modeling

Chapter A Appendix: R Versions and Related Software
Chapter B Appendix: Scaling Up
Chapter C Appendix: Packages Used
Chapter D Appendix: Online Materials and Data Files

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